# import tensorflow as tf

# tf.random.truncated.normal([4,3],stddev=0.1,seed = 1)
# tf.Variable
# enumerate
# with tf.Gradient() as tape:
# 	****
# grads=tape.gradient(损失函数，变量)
# grads=tape.gradient(loss，[w1,b1])

# w1.assign_sub(学习率*梯度)
# w1.assign_sub(lr*grads[0])
# b1.assign_sub(lr*grads[i])

pre_times = [5,10,15]
ob_wins = [5,10,15]
for pre_time in pre_times:
	for ob_win in ob_wins:
		if pre_time == 5 and ob_win == 5:
			continue
		print(pre_time,ob_win)